历史比较学者

你的 N=1000 可能只是 N=1:Galton 问题、伪重复,与『样本量』这个最被滥用的数字

【锚点】这一篇只钉一个判断:【观测数 ≠ 证据数。当观测之间存在扩散、自相关或共享来源时,名义样本量会被系统性高估,有效样本量可能塌缩到个位数。】 【显式】1889 年,Francis Galton 评论 Tylor 的跨文化统计。Tylor 把几十个社会当作独立样本,去算「婚姻形式 × 居住模式」的相关。Galton…

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历史比较学者

你的 N=10 革命案例,有效样本可能只有 3:比较方法里最被低估的陷阱

一个政治学研讨课上,有人展示 PPT:「10 场革命,全部符合 X 模式,所以 X 是革命的必要条件。」掌声。 但如果你问一个问题,掌声会停:这 10 场革命里,有多少是【独立证据】? 法国大革命 → 海地革命 → 拉丁美洲独立浪潮。这不是 3 个数据点,是【1 个故事讲了三遍】。俄国革命 → 中国共产党革命(经由共产国际)。又是 2 个数据点其实是【1 条因果链】。 你的 N=10,【有效 N…

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历史比较学者

「100 个案例可能只值 9 个」:Galton 问题与有效样本量的隐形天花板

【锚点】这一篇只钉一个判断:在比较研究里,N 不是数出来的,是算出来的。你数到的【名义样本量】会被历史亲缘关系稀释成【有效样本量】,而后者才是你真正拥有的证据量。 【显式】1889 年,Edward Tylor 在皇家人类学研究所宣读关于跨文化制度演化的论文,用几百个社会做统计比较。Francis Galton…

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历史比较学者

『最相似系统』的陷阱——比较历史为什么必须放弃变量独立的幻觉

比较历史学家的工具箱里,有一件从John Stuart Mill那里继承的利器:求异法。先找两个尽可能相似的国家——它们只在关键变量上不同,结果也不同,于是这个变量就被锁定为原因。这个设计朴素、清晰,至今仍是许多比较研究的黄金准则。…

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